Code
library(leaflet)
leaflet() %>%
addTiles() %>% # Add default OpenStreetMap map tiles
addMarkers(lng = -64.050, lat = -64.773, popup = "Palmer Archipelago, Antarctica")Figure 1: Palmer Archipelago, Antarctica.
Please Read
This report has been created as a learning exercise on how to generate interactive and engaging reports using Quarto.
It demonstrates the integration of various R packages for data exploration, visualization, and data analysis, with a focus on creating a dynamic and user-friendly report layout.
The use of interactive elements, such as tabs, tables, and visualizations, is emphasized to showcase the versatility of Quarto in producing polished and professional reports.
Disclaimer
This report is intended solely for educational purposes. The analyses and interpretations provided here are based on the Palmer Penguins dataset and serve as examples to practice data analysis and visualization techniques.
1 Introduction
The objective of this report is to demonstrate a data analysis workflow using the palmerpenguins package, which offers an excellent dataset for data exploration and visualization.
1.1 Palmer Penguins
The package contains data on 344 penguins across three species, collected from three different islands in the Palmer Archipelago, Antarctica1. The data was gathered by Dr. Kristen Gorman and the Palmer Station, Antarctica LTER2.
These beautifully crafted illustrations were designed by Allison Horst. Visit her page here.
1.2 Setting Up the Environment
This analysis requires several packages. The following packages will be used throughout the report for data manipulation, visualization, and data analysis.
Code
library(palmerpenguins)
library(tidyverse)
library(DT)
library(ggplot2)- 1
- To use dataset for analysis.
- 2
- For data manipulation and visualization.
- 3
- To create interactive data tables.
- 4
- For creating customizable visualizations.
2 Exploratory Data Analysis
Let’s dive deeper into the penguins dataset to explore its features and structure.
2.1 Summary of Dataset
Code
data("penguins")
summary(penguins) species island bill_length_mm bill_depth_mm
Adelie :152 Biscoe :168 Min. :32.10 Min. :13.10
Chinstrap: 68 Dream :124 1st Qu.:39.23 1st Qu.:15.60
Gentoo :124 Torgersen: 52 Median :44.45 Median :17.30
Mean :43.92 Mean :17.15
3rd Qu.:48.50 3rd Qu.:18.70
Max. :59.60 Max. :21.50
NA's :2 NA's :2
flipper_length_mm body_mass_g sex year
Min. :172.0 Min. :2700 female:165 Min. :2007
1st Qu.:190.0 1st Qu.:3550 male :168 1st Qu.:2007
Median :197.0 Median :4050 NA's : 11 Median :2008
Mean :200.9 Mean :4202 Mean :2008
3rd Qu.:213.0 3rd Qu.:4750 3rd Qu.:2009
Max. :231.0 Max. :6300 Max. :2009
NA's :2 NA's :2 The Palmer Penguins dataset contains 344 penguins from three distinct species: Adelie (152), Chinstrap (68), and Gentoo (124). These penguins were observed on three islands within the Palmer Archipelago: Biscoe, Dream, and Torgersen.
The dataset includes several key measurements:
The bill length, which ranges from 32.1 mm to 59.6 mm with an average of 43.92 mm, and
The bill depth, ranging from 13.1 mm to 21.5 mm, with an average of 17.15 mm.
The flipper length varies between 172 mm and 231 mm, averaging 200.9 mm.
The body mass ranges from 2700 g to 6300 g, with a mean of 4202 g.
The dataset provides information on the sex of the penguins, with 165 females and 168 males, though 11 entries for sex are missing.
The data was collected over three years: 2007, 2008, and 2009, with a few missing values for bill length and bill depth (2 entries each).
2.2 Descriptive Tables
The DT package allows us to create an interactive table that enables filtering, searching, and sorting based on specific columns, offering a dynamic way to explore the dataset further.
Code
datatable(penguins, filter = "top")3 Data Visualization
Let us explore various visualizations that can be generated from the Palmer Penguins dataset using the ggplot2 package. These visualizations, inspired by Allison Horst, provide insights into the relationships between key variables.
3.1 Penguin Mass vs. Flipper Length
Code
mass_flipper <- ggplot(data = penguins,
aes(x = flipper_length_mm,
y = body_mass_g)) +
geom_point(aes(color = species,
shape = species),
size = 3,
alpha = 0.8) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(title = "Penguin size, Palmer Station LTER",
subtitle = "Flipper length and body mass for Adelie, Chinstrap and Gentoo Penguins",
x = "Flipper length (mm)",
y = "Body mass (g)",
color = "Penguin species",
shape = "Penguin species") +
theme(legend.position = c(0.2, 0.7),
plot.title.position = "plot",
plot.caption = element_text(hjust = 0, face= "italic"),
plot.caption.position = "plot")
mass_flipper
This graph illustrates the relationship between flipper length and body mass for three penguin species: Adelie, Chinstrap, and Gentoo, based on data collected at Palmer Station LTER. This visualization highlights the species-specific differences in body mass and flipper length.
3.2 Flipper Length vs. Bill Length
Code
flipper_bill <- ggplot(data = penguins,
aes(x = flipper_length_mm,
y = bill_length_mm)) +
geom_point(aes(color = species,
shape = species),
size = 3,
alpha = 0.8) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(title = "Flipper and bill length",
subtitle = "Dimensions for Adelie, Chinstrap and Gentoo Penguins at Palmer Station LTER",
x = "Flipper length (mm)",
y = "Bill length (mm)",
color = "Penguin species",
shape = "Penguin species") +
theme(legend.position = c(0.85, 0.15),
plot.title.position = "plot",
plot.caption = element_text(hjust = 0, face= "italic"),
plot.caption.position = "plot")
flipper_bill
This graph visualizes the relationship between flipper length (mm) and bill length (mm) for three penguin species. It highlights species-specific variations in bill and flipper length, showing that Gentoo penguins tend to have the longest flippers, while Chinstrap penguins exhibit the greatest variability in bill length.
3.3 Bill Length vs. Bill Depth
Code
bill_len_dep <- ggplot(data = penguins,
aes(x = bill_length_mm,
y = bill_depth_mm,
group = species)) +
geom_point(aes(color = species,
shape = species),
size = 3,
alpha = 0.8) +
geom_smooth(method = "lm", se = FALSE, aes(color = species)) +
scale_color_manual(values = c("darkorange","purple","cyan4")) +
labs(title = "Penguin bill dimensions",
subtitle = "Bill length and depth for Adelie, Chinstrap and Gentoo Penguins at Palmer Station LTER",
x = "Bill length (mm)",
y = "Bill depth (mm)",
color = "Penguin species",
shape = "Penguin species") +
theme(legend.position = c(0.85, 0.15),
plot.title.position = "plot",
plot.caption = element_text(hjust = 0, face= "italic"),
plot.caption.position = "plot")
bill_len_dep
This graph illustrates the relationship between bill length (mm) and bill depth (mm) for three penguin species. Each species is color-coded and shown with distinct shapes. The trend lines are fitted for each species to show the linear relationship between bill length and depth.
`geom_smooth()` using formula = 'y ~ x'
3.4 Using Tabs for Multiple Graphs
Including multiple graphs in a report can sometimes make it feel cluttered. By organizing the graphs into tabs, we give readers the flexibility to easily navigate and view only the visualizations they are interested in. This approach keeps the report clean and more user-friendly, allowing for a better browsing experience.
Footnotes
The Palmer Archipelago is a group of islands located off the northwestern coast of the Antarctic Peninsula.↩︎
The Long Term Ecological Research (LTER) network is a collaborative program that conducts long-term studies to monitor and understand ecological processes. The Palmer Station in Antarctica is part of this network, conducting critical research on the region’s unique ecosystem.↩︎